Tall trees are key drivers of ecosystem processes in tropical forest, but the controls on the distribution of the very tallest trees remain poorly understood. The recent discovery of grove of giant trees over 80 meters tall in the Amazon forest requires a reevaluation of current thinking. We used high-resolution airborne laser surveys to measure canopy height across 282,750 ha of old-growth and second-growth forests randomly sampling the entire Brazilian Amazon. We investigated how resources and disturbances shape the maximum height distribution across the Brazilian Amazon through the relations between the occurrence of giant trees and environmental factors. Common drivers of height development are fundamentally different from those influencing the occurrence of giant trees. We found that changes in wind and light availability drive giant tree distribution as much as precipitation and temperature, together shaping the forest structure of the Brazilian Amazon. The location of giant trees should be carefully considered by policymakers when identifying important hot spots for the conservation of biodiversity in the Amazon.

Background: Brazilian Amazon forests contain a large stock of carbon that could be released into the atmosphere as a result of land use and cover change. To quantify the carbon stocks, Brazil has forest inventory plots from different sources, but they are unstandardized and not always available to the scientific community. Considering the Brazilian Amazon extension, the use of remote sensing, combined with forest inventory plots, is one of the best options to estimate forest aboveground biomass (AGB). Nevertheless, the combination of limited forest inventory data and different remote sensing products has resulted in significant differences in the spatial distribution of AGB estimates. This study evaluates the spatial coverage of AGB data (forest inventory plots, AGB maps and remote sensing products) in undisturbed forests in the Brazilian Amazon. Additionally, we analyze the interconnection between these data and AGB stakeholders producing the information. Specifically, we provide the first benchmark of the existing field plots in terms of their size, frequency, and spatial distribution. Results:We synthesized the coverage of forest inventory plots, AGB maps and airborne light detection and ranging (LiDAR) transects of the Brazilian Amazon. Although several extensive forest inventories have been implemented, these AGB data cover a small fraction of this region (e.g., central Amazon remains largely uncovered). Although the use of new technology such as airborne LiDAR cover a significant extension of AGB surveys, these data and forest plots represent only 1% of the entire forest area of the Brazilian Amazon. Conclusions:Considering that several institutions involved in forest inventories of the Brazilian Amazon have different goals, protocols, and time frames for forest surveys, forest inventory data of the Brazilian Amazon remain unstandardized. Research funding agencies have a very important role in establishing a clear sharing policy to make data free and open as well as in harmonizing the collection procedure. Nevertheless, the use of old and new forest inventory plots combined with airborne LiDAR data and satellite images will likely reduce the uncertainty of the AGB distribution of the Brazilian Amazon.

Very few studies have been devoted to understanding the digital terrain model (DTM) creation for Amazon forests. DTM has a special and important role when airborne laser scanning is used to estimate vegetation biomass. We examined the influence of pulse density, spatial resolution, filter algorithms, vegetation density and slope on the DTM quality. Three Amazonian forested areas were surveyed with airborne laser scanning, and each original point cloud was reduced targeting to 20, 15, 10, 8, 6, 4, 2, 1, 0.75, 0.5 and 0.25 pulses per square meter based on a random resampling process. The DTM from resampled clouds was compared with the reference DTM produced from the original LiDAR data by calculating the deviation pixel by pixel and summarizing it through the root mean square error (RMSE). The DTM from resampled clouds were also evaluated considering the level of agreement with the reference DTM. Our study showed a clear trade-off between the return density and the horizontal resolution. Higher forest canopy density demanded higher return density or lower DTM resolution.

To effectively implement the Paris Agreement, capacity in carbon accounting must be strengthened in the developing world, and partnerships with local academic institutions can do the accounting for governments and fill the capacity gap. This paper highlights the Brazilian case, focusing on ways in which climate change science information and transparency are being incorporated in national C accounting initiatives, particularly the national inventory of greenhouse gas (GHG) emissions and removals. We report how the third inventory for the sector of land use, land-use change and forestry (LULUCF) was implemented to address scientific challenges involved in the monitoring of carbon stocks and land-use changes of diverse and complex biomes while addressing international and national policy demands (report and decision support) and transparency to various stakeholders. GHG emissions and removals associated with 2002-2010 carbon changes in aboveground, belowground biomass, necromass and soil carbon by land use and land cover changes were estimated for all Brazilian biomes, and for the Amazon estimates were also presented for the periods of 2002-2005 and 2005-2010. The inventory improved regional estimates for carbon stock and national emission factors with the support and engagement of the scientific community. Incorporation of local context is essential to reduce uncertainties and properly monitor efforts to contribute to GHG emission/reduction targets. To promote transparency and make information more accessible, the national inventory results were made available by the National Emissions Registry System (SIRENE). This system was built to support climate change policies as an important legal apparatus and by increasing access to emissions and land-use change data.

The paper "Are Brazil deforesters avoiding detection?" recently published in Conservation Letters by Richards et al. 2016 has critical shortcomings and conclusions based on biased and not very robust analyses. Here, we provide clarifications to some of the most critical points regarding the monitoring of land use changes in the Brazilian Amazon and related greenhouse emissions.